class_docstr: Class wrapping the normalizing flows so it can articulate with
  :class:`~pythae.trainers.BaseTrainer`
code: def __init__(self, prior: torch.distributions, flow: BaseNF):
      nn.Module.__init__(self)
      self.prior = prior
      self.flow = flow
  
imports: import os
  import sys
  from copy import deepcopy
  import numpy
  import torch
  import torch.nn
  from ....data.datasets import BaseDataset
  from ...auto_model import AutoConfig
  from ...base.base_config import EnvironmentConfig
  from ...base.base_utils import ModelOutput
  from .base_nf_config import BaseNFConfig
label_desc: Use image node_id 1 to create a new NFModel object from inherited base classes: nn with example: obj = NFModel(prior, flow)